Source: thenewstack.io
GitLab Brings on UnReview to Solve Code Review, Address AI/ML DevOpsCategory: gitlab, artificial-intelligence
On the first point, GitLab senior director David DeSanto explained that GitLab wants to: reduce friction, improve experience, better security, and generally increase efficiency.
When you look at that as a process, that could be a very laborious process for the developer and for the reviewer.
Part of the hitch there is that it takes a lot of infrastructure to build, train, and manage ML models.
This is kind of putting the flag in the ground and saying, ‘We as GitLab see that ML and AI cannot be an external part of the DevOps toolchain, it actually has to be embedded in from the beginning,'” said DeSanto.
Already, DeSanto said that GitLab has built a proof of concept that it is using internally to help ensure the right labels are being applied to issues, with issues correctly assigned, using ML/AI.
When you look at that as a process, that could be a very laborious process for the developer and for the reviewer.
Part of the hitch there is that it takes a lot of infrastructure to build, train, and manage ML models.
This is kind of putting the flag in the ground and saying, ‘We as GitLab see that ML and AI cannot be an external part of the DevOps toolchain, it actually has to be embedded in from the beginning,'” said DeSanto.
Already, DeSanto said that GitLab has built a proof of concept that it is using internally to help ensure the right labels are being applied to issues, with issues correctly assigned, using ML/AI.
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